Dataset Information

Development and validation of a simplified Stroke-Thrombolytic Predictive Instrument.

ABSTRACT:

Objectives

The Stroke-Thrombolytic Predictive Instrument (Stroke-TPI) predicts the probability of good and bad outcomes with and without recombinant tissue plasminogen activator (rtPA). We sought to rebuild and externally validate a simpler Stroke-TPI to support implementation in routine clinical care.

Methods

Using the original derivation cohort of 1,983 patients from a combined database of randomized clinical trials (NINDS [National Institute of Neurological Disorders and Stroke] 1 and 2; ATLANTIS [Alteplase Thrombolysis for Acute Noninterventional Therapy in Ischemic Stroke] A and B; and ECASS [European Cooperative Acute Stroke Study] II), we simplified the Stroke-TPI by reducing variables and interaction terms and by exploring simpler (3- and 8-item) stroke severity scores. External validation was performed in the ECASS III trial (n = 821).

Results

The following 6 variables were most predictive of good outcomes: age, systolic blood pressure, diabetes, stroke severity, symptom onset to treatment time, and rtPA therapy. Treatment effect modifiers included onset to treatment time and systolic blood pressure. For the models predicting a bad outcome (modified Rankin Scale [mRS] score ?5), significant variables included age, stroke severity, and serum glucose. rtPA therapy did not change the risk of a poor outcome. Compared with models using the full NIH Stroke Scale, models using the 3-item severity score showed similar discrimination and excellent calibration. External validation on ECASS III showed similar performance (C statistics 0.75 [mRS score ?1] and 0.80 [mRS score ?2]).

Conclusion

A simpler model using a 3-item stroke severity score, instead of the 15-item NIH Stroke Scale, has similar prognostic value and may be easier to use in routine care. Future studies are needed to test whether it can improve process and clinical outcomes.

SUBMITTER: Kent DM

PROVIDER: S-EPMC4567461 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development and validation of a simplified Stroke-Thrombolytic Predictive Instrument.

Kent David M DM Ruthazer Robin R Decker Carole C Jones Philip G PG Saver Jeffrey L JL Bluhmki Erich E Spertus John A JA

Neurology 20150819 11

<h4>Objectives</h4>The Stroke-Thrombolytic Predictive Instrument (Stroke-TPI) predicts the probability of good and bad outcomes with and without recombinant tissue plasminogen activator (rtPA). We sought to rebuild and externally validate a simpler Stroke-TPI to support implementation in routine clinical care.<h4>Methods</h4>Using the original derivation cohort of 1,983 patients from a combined database of randomized clinical trials (NINDS [National Institute of Neurological Disorders and Stroke ...[more]

PMID: 26291280

Similar Datasets

Project description:Background: Mortality from multidrug-resistant (MDR) pathogens is an urgent healthcare crisis worldwide. At present we do not have any simplified screening tools to predict the risk of mortality associated with MDR infections. The aim of this study was to develop a screening tool to predict mortality in patients with multidrug-resistant organisms. Methods: A retrospective cohort study to evaluate mortality risks in patients with MDR infections was conducted at Phrae Hospital. Univariable and multivariable analyses were used to classify possible risk factors. The model performance was internally validated utilizing the mean of three measures of discrimination corrected by the optimism using a 1000-bootstrap procedure. The coefficients were transformed into item scores by dividing each coefficient with the lowest coefficient and then rounding to the most adjacent number. The area under the receiver operating characteristic curve (AuROC) was used to determine the performance of the model. Results: Between 1 October 2018 and 30 September 2020, a total of 504 patients with MDR infections were enrolled. The ICU-SEPSA score composed of eight clinical risk factors: 1) immunocompromised host, 2) chronic obstructive pulmonary disease, 3) urinary tract infection, 4) sepsis, 5) placement of endotracheal tube, 6) pneumonia, 7) septic shock, and 8) use of antibiotics within the past 3 months. The model showed good calibration (Hosmer-Lemeshow χ2 = 19.27; p-value = 0.50) and good discrimination after optimism correction (AuROC 84.6%, 95% confidence interval [Cl]: 81.0%–88.0%). The positive likelihood ratio of low risk (score ≤ 5) and high risk (score ≥ 8) were 2.07 (95% CI: 1.74–2.46) and 12.35 (95% CI: 4.90–31.13), respectively. Conclusion: A simplified predictive scoring tool wad developed to predict mortality in patients with MDR infections. Due to a single-study design of this study, external validation of the results before applying in other clinical practice settings is warranted.

Project description:Background: Hemorrhagic transformation (HT) after reperfusion therapy for acute ischemic stroke (AIS) has been well studied; however, there is scarce research focusing on spontaneous HT (sHT). Spontaneous HT is no less important with a relatively high incidence and could be associated with neurological worsening. We aimed to develop and validate a simple and practical model to predict sHT after AIS (SHAIS) and compared the predictive value of the SHAIS score against the models of post-Reperfusion HT for sHT. Methods: Patients with AIS admitted within 24 h of onset were prospectively screened to develop and validate the SHAIS score. The primary outcome was sHT during hospitalization (within 30 days after onset), and the secondary outcomes were symptomatic sHT and parenchymal hematoma (PH). Clinical information, laboratory, and neuroimaging data were screened to construct the SHAIS score. We selected six commonly used scales for predicting HT after reperfusion therapy and compared their predictive ability for sHT with the SHAIS score using Delong's test. Results: The derivation cohort included 539 patients (mean age, 68.1 years; men, 61.4%), of whom 91 (16.9%) patients developed sHT with 25.3% (23/91) being symptomatic sHT and 62.6% (57/91) being PH. Five variables (atrial fibrillation, NIHSS score ≥ 10, hypodensity > 1/3 of middle cerebral artery territory, hyperdense artery sign, and anterior circulation infarction) composed the SHAIS score, which ranged from 0 to 11 points. The area under the receiver-operating characteristic curve (AUC) was 0.86 (95% CI 0.82-0.91, p < 0.001) for the overall sHT, 0.85 (95% CI 0.76-0.92, p < 0.001) for symptomatic sHT, and 0.89 (95% CI 0.85-0.94, p < 0.001) for PH. No evidence of miscalibration of the SHAIS score was found to predict the overall sHT (p = 0.19), symptomatic sHT (p = 0.44), and PH (p = 0.22). The internal (n = 245) and external validation cohorts (n = 200) depicted similar predictive performance compared to the derivation cohort. The SHAIS score had a higher AUC to predict sHT than any of the six pre-Existing models (p < 0.05). Conclusions: The SHAIS score provides an easy-to-use model to predict sHT, which could help providers with decision-making about treatments with high bleeding risk, and to counsel patients and families on the baseline risk of HT, aligning expectations with probable outcomes.

Project description:IntroductionThis study aimed at generating a new simplified prognostic score (SPS) using common clinical and biological variables to discriminate a limited number of subgroups of patients with SCLC differing by their overall survival (OS).MethodsThe SPS was developed exploring the Montpellier University Hospital retrospective database of 401 patients over a 16-year period. All patients had received etoposide - platinum-based chemotherapy as first-line treatment. The SPS development took into account significant determinants of OS in the Cox model, weighted by their regression β coefficients. Validation of the consequent SPS has been done separately in a combined population of 213 patients accrued from two different published trials (NCT03059667 and NCT00930891).ResultsThe significant independent determinants of OS included the following: (1) American Joint Committee on Cancer TNM stage IV (hazard ratio [HR]: 2.52; 95% confidence interval [CI]: 1.91-3.33); (2) Eastern Cooperative Oncology Group performance status greater than 1 (HR: 2.27; 95% CI: 1.79-2.87); (3) the presence of liver metastases (HR: 1.66; 95% CI: 1.29-2.15); and (4) neutrophil-to-lymphocyte ratio greater than 4 (HR: 1.39; 95% CI: 1.11-1.92). The SPS generated with these four variables, segregated three groups (good, intermediate, and poor prognosis) with respective median OS of 26.9 months (95% CI: 20.1-38.9), 11.5 months (95% CI: 9.8-13.0), and 6.8 months (95% CI: 5.8-8.3; log-rank p < 10-4). Harrell's C statistic estimate was 0.68 ± 0.012, suggesting goodness of calibration. In the validation cohort, the SPS segregated the aforementioned three subgroups in a nearly similar manner, with respective median OS: 27.2, 12.3, and 8.6 months (log-rank p < 10-3; Harrell's C statistic: 0.58 ± 0.02).ConclusionsThe SPS is easy to calculate in real-life practice and efficiently discriminates three populations with different prognoses. This study deserves further validation of this score in patients with SCLC receiving immunochemotherapy.

Project description:BackgroundThis paper describes the development of the Chinese Quality of Life Instrument (ChQOL) which is a self-report health status instrument. Chinese Medicine relies very much on asking subjective feelings of patients in the process of diagnosis and monitoring of treatment. For thousands of years, Chinese Medicine practitioners have accumulated a good wealth of experiences in asking questions about health of their patients based on the concept of health in Chinese Medicine. These experiences were then transformed into questions for the ChQOL. It is believed that ChQOL can contribute to the existing Patient Report Outcome measures. This paper outlines the concept of health and disease in Traditional Chinese Medicine, the building of the conceptual framework of the ChQOL, the steps of drafting, selecting and validating the items, and the psychometric properties of the ChQOL.MethodsThe development of the ChQOL was based on the concept of health in Traditional Chinese Medicine with a theory driven approach. Based on the results of literature review, the research team developed an initial model of health which encompassed the concept of health in TCM. An expert panel was then invited to comment and give suggestions for improvement of the initial model. According to their suggestions, the model was refined and a set of initial items for the ChQOL was drafted. The refined model, together with the key domains, facets and initial items of the ChQOL were then mailed to a sample of about 100 Chinese medicine practitioners throughout Mainland China for their comments and advice. A revised set of items were developed for linguistic testing by a convenience sample consisting of both healthy people and people who attended Chinese Medicine treatment. After that, an item pool was developed for field-testing. Field test was conducted on a convenience sample of healthy and patient subjects to determine the construct validity and psychometric properties of the ChQOL.ResultsConstruct validity was established by various methods, i.e. the internal consistency in all facets and domains were good; the correlation between facets to domain, and domains to overall ChQOL correlation were high; confirmatory factor analysis showed that the structure fitness of all facets, domain and overall structure were good with CFI > 0.9. Test-retest reliability was also good, especially in the domain scores with ICC value ranging from 0.83 to 0.90. No ceiling or floor effect was noted which indicated that ChQOL can be applied to subjects with a wide range of health status. Most facet scores, domain scores and the overall CHQOL scores were able to discriminate groups of subjects with known differences in health status. The ChQOL had mild positive convergence with the other generic health related QOL measures, i.e. the WHOQOL-100 and the SF-36, with moderate correlations.ConclusionIn conclusion, the study indicated that the ChQOL is conceptually valid with satisfactory psychometric properties. It can provide additional information on health and QOL on top of the existing generic health related QOL measures. Furthermore, it forms basis for further testing and applications in clinical trials.

Dataset Information

Development and validation of a simplified Stroke-Thrombolytic Predictive Instrument.

Objectives

Methods

Results

Conclusion

Publications

Development and validation of a simplified Stroke-Thrombolytic Predictive Instrument.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets